Your company has a stateless web API that performs scientific calculations. The web API runs on a single Google Kubernetes Engine (GKE) cluster. The cluster is currently deployed in us-centralYour company has expanded to offer your API to customers in Asia. You want to reduce the latency for users in Asia. What should you do?

Creating a second GKE cluster in asia-southeast1 brings the API closer to users in Asia, reducing latency. kubemci (Kubernetes Multi-Cluster Ingress) is a tool that allows you to deploy a single global HTTP(S) Load Balancer across multiple GKE clusters in different regions. This load balancer automatically directs user traffic to the closest healthy cluster, optimizing performance and providing high availability. Using a Service of type LoadBalancer for each cluster and adding public IPs to Cloud DNS would provide regional load balancing but wouldn't offer the global traffic management and single IP endpoint of an HTTP(S) Load Balancer. A global HTTP(S) load balancer with Cloud CDN enabled is suitable for static content, but the API performs dynamic scientific calculations, making CDN less effective for the core API logic. Increasing memory and CPU only scales the existing cluster and doesn't address the latency issue for geographically distant users.